Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 143,547
2 Rhode Island 142,290
3 South Dakota 139,965
4 Utah 125,855
5 Tennessee 123,672
6 Arizona 120,159
7 Iowa 117,267
8 Wisconsin 115,259
9 Nebraska 115,113
10 South Carolina 114,492
11 Oklahoma 114,095
12 New Jersey 113,957
13 Arkansas 112,467
14 Delaware 110,835
15 Alabama 110,314
16 Indiana 110,010
17 Illinois 108,446
18 Kansas 108,000
19 New York 107,327
20 Florida 107,068
21 Idaho 106,758
22 Mississippi 106,140
23 Minnesota 105,730
24 Nevada 104,447
25 Montana 103,945
26 Georgia 102,940
27 Wyoming 102,591
28 Kentucky 102,180
29 Massachusetts 102,037
30 Texas 101,290
31 Louisiana 100,467
32 Missouri 99,424
33 Michigan 98,274
34 Connecticut 97,032
35 New Mexico 96,092
36 California 95,482
37 North Carolina 95,442
38 Alaska 94,575
39 Ohio 93,551
40 Pennsylvania 93,318
41 Colorado 93,230
42 West Virginia 88,803
43 Virginia 78,650
44 Maryland 75,583
45 New Hampshire 72,057
46 District of Columbia 68,911
47 Washington 56,067
48 Puerto Rico 53,449
49 Maine 49,333
50 Oregon 46,670
51 Vermont 38,442
52 Hawaii 24,293

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 Delaware 315
2 Michigan 200
3 Wyoming 171
4 Louisiana 159
5 Idaho 149
6 Maine 148
7 New Mexico 133
8 Mississippi 132
9 Alaska 131
10 North Carolina 131
11 Colorado 127
12 Nevada 127
13 West Virginia 126
14 Florida 117
15 North Dakota 112
16 Rhode Island 110
17 Illinois 108
18 Tennessee 108
19 Pennsylvania 106
20 Minnesota 103
21 Washington 103
22 Kentucky 99
23 Kansas 98
24 Montana 98
25 Oregon 91
26 Connecticut 90
27 Indiana 90
28 Texas 88
29 Utah 88
30 Wisconsin 83
31 Ohio 75
32 Arizona 74
33 New Hampshire 74
34 New York 72
35 Arkansas 68
36 Missouri 68
37 South Dakota 67
38 Iowa 65
39 Georgia 61
40 Massachusetts 60
41 Nebraska 58
42 South Carolina 57
43 Vermont 56
44 Alabama 54
45 New Jersey 53
46 Oklahoma 52
47 Hawaii 50
48 Puerto Rico 44
49 Virginia 44
50 District of Columbia 42
51 Maryland 41
52 California 33

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 2,929
2 New York 2,698
3 Massachusetts 2,581
4 Rhode Island 2,551
5 Mississippi 2,442
6 Arizona 2,403
7 Connecticut 2,301
8 Louisiana 2,260
9 South Dakota 2,253
10 Alabama 2,252
11 Pennsylvania 2,107
12 North Dakota 2,015
13 Indiana 2,007
14 Michigan 1,994
15 New Mexico 1,966
16 Illinois 1,962
17 Arkansas 1,923
18 Iowa 1,907
19 South Carolina 1,877
20 Georgia 1,876
21 Nevada 1,800
22 Tennessee 1,794
23 Texas 1,767
24 Oklahoma 1,748
25 Kansas 1,746
26 Delaware 1,696
27 Florida 1,688
28 Ohio 1,679
29 District of Columbia 1,592
30 California 1,588
31 Missouri 1,556
32 West Virginia 1,543
33 Kentucky 1,532
34 Montana 1,498
35 Maryland 1,481
36 Wisconsin 1,327
37 Minnesota 1,315
38 Virginia 1,294
39 North Carolina 1,235
40 Wyoming 1,231
41 Nebraska 1,223
42 Idaho 1,161
43 Colorado 1,147
44 New Hampshire 985
45 Puerto Rico 767
46 Washington 751
47 Utah 709
48 Oregon 622
49 Maine 600
50 Alaska 481
51 Vermont 408
52 Hawaii 345

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 Missouri 8
2 Alaska 7
3 Michigan 4
4 Florida 3
5 Oklahoma 3
6 Connecticut 2
7 Louisiana 2
8 New Jersey 2
9 North Carolina 2
10 Ohio 2
11 Pennsylvania 2
12 Tennessee 2
13 Washington 2
14 Arizona 1
15 Arkansas 1
16 Colorado 1
17 District of Columbia 1
18 Georgia 1
19 Illinois 1
20 Indiana 1
21 Iowa 1
22 Kansas 1
23 Kentucky 1
24 Maine 1
25 Maryland 1
26 Massachusetts 1
27 Minnesota 1
28 Mississippi 1
29 Montana 1
30 Nevada 1
31 New Hampshire 1
32 New Mexico 1
33 New York 1
34 Oregon 1
35 Puerto Rico 1
36 South Dakota 1
37 Texas 1
38 Utah 1
39 Vermont 1
40 Virginia 1
41 West Virginia 1
42 Wisconsin 1
43 Alabama 0
44 California 0
45 Delaware 0
46 Hawaii 0
47 Idaho 0
48 North Dakota 0
49 Rhode Island 0
50 South Carolina 0
51 Wyoming 0
52 Nebraska -1

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Chattahoochee Georgia 375,355 1 99
Crowley Colorado 362,976 2 99
Bent Colorado 275,596 3 99
Dewey South Dakota 250,000 4 99
Lincoln Arkansas 246,084 5 99
Davidson Tennessee 142,606 188 94
Richland South Carolina 112,770 983 68
York South Carolina 112,115 1015 67
Orange California 85,468 2240 28
Pierce Washington 58,531 2850 9

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Foard Texas 8,658 1 99
Galax city Virginia 8,350 2 99
Jerauld South Dakota 7,948 3 99
Emporia city Virginia 7,856 4 99
Hancock Georgia 7,804 5 99
Orange California 1,585 1830 41
York South Carolina 1,363 2084 33
Davidson Tennessee 1,361 2089 33
Richland South Carolina 1,349 2109 32
Pierce Washington 741 2742 12

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons